Abhigyan Nath

Orcid: 0000-0003-1253-7115

According to our database1, Abhigyan Nath authored at least 15 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Bibliography

2024
A novel intuitionistic fuzzy rough instance selection and attribute reduction with kernelized intuitionistic fuzzy C-means clustering to handle imbalanced datasets.
Expert Syst. Appl., 2024

2022
Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity.
Medical Biol. Eng. Comput., 2022

2021
Prediction for understanding the effectiveness of antiviral peptides.
Comput. Biol. Chem., 2021

2020
A representation transfer learning approach for enhanced prediction of growth hormone binding proteins.
Comput. Biol. Chem., 2020

Improved cytokine-receptor interaction prediction by exploiting the negative sample space.
BMC Bioinform., 2020

2019
Prediction and molecular insights into fungal adhesins and adhesin like proteins.
Comput. Biol. Chem., 2019

2018
The role of pertinently diversified and balanced training as well as testing data sets in achieving the true performance of classifiers in predicting the antifreeze proteins.
Neurocomputing, 2018

2017
Enhanced Prediction for Observed Peptide Count in Protein Mass Spectrometry Data by Optimally Balancing the Training Dataset.
Int. J. Pattern Recognit. Artif. Intell., 2017

Enhanced identification of β-lactamases and its classes using sequence, physicochemical and evolutionary information with sequence feature characterization of the classes.
Comput. Biol. Chem., 2017

2016
Unsupervised learning assisted robust prediction of bioluminescent proteins.
Comput. Biol. Medicine, 2016

2015
Identification of human drug targets using machine-learning algorithms.
Comput. Biol. Medicine, 2015

Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.
Comput. Biol. Chem., 2015

Effect of varying degree of resampling on prediction accuracy for observed peptide count in protein mass spectrometry data.
Proceedings of the 11th International Conference on Natural Computation, 2015

2014
Inferring biological basis about psychrophilicity by interpreting the rules generated from the correctly classified input instances by a classifier.
Comput. Biol. Chem., 2014

2013
An insight into the molecular basis for convergent evolution in fish antifreeze Proteins.
Comput. Biol. Medicine, 2013


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